finam.data

Specialized data types for exchanges between models/modules.

Grids

Grid tools

check_axes_monotonicity(axes)	Check axes to be strictly monotonic, and makes them strictly monotonic increasing.
check_axes_uniformity(axes)	Check axes to be uniform.
check_uniformity(values)	Checks for uniform spacing of values

Grid abstract base classes

GridBase()	Abstract grid base.
Grid()	Abstract grid specification.
StructuredGrid()	Abstract structured grid specification.

Data tools

assert_type(cls, slot, obj, types)	Type assertion.
check(xdata, info)	Check if data matches given info.
check_quantified(xdata[, routine])	Check if data is a quantified DataArray.
full(value, info)	Return a new data array with units according to the given info, filled with given value.
full_like(xdata, value)	Return a new data array with the same shape, type and units as a given object.
get_dimensionality(xdata)	Get dimensionality of the data.
get_magnitude(xdata)	Get magnitude of given data.
get_units(xdata)	Get units of the data.
has_time_axis(xdata, grid)	Check if the data array has a time axis.
is_quantified(xdata)	Check if data is a quantified DataArray.
prepare(data, info[, time_entries, ...])	Prepares data in FINAM's internal transmission format.
quantify(xdata[, units])	Quantifies data.
strip_time(xdata, grid)	Returns a view of the data with the time dimension squeezed if there is only a single entry
to_datetime(date)	Converts a numpy datetime64 object to a python datetime object
to_units(xdata, units[, check_equivalent, ...])	Convert data to given units.
is_masked_array(data)	Check if data is a masked array.
has_masked_values(data)	Determine whether the data has masked values.
filled(data[, fill_value])	Return input as an array with masked data replaced by a fill value.
to_masked(data, **kwargs)	Return a masked version of the data.
to_compressed(xdata[, order])	Return all the non-masked data as a 1-D array respecting the given array order.
from_compressed(xdata, shape[, order])	Fill a (masked) array following a given mask or shape with the provided data.
check_data_covers_domain(data[, mask])	Check if the given data covers a domain defined by a mask on the same grid.